Pair programming is an agile software development technique in which two programmers work together at one workstation. One, the driver, writes code while the other, the observer or navigator, reviews each line of code as it is typed in. The two programmers switch roles frequently.
While reviewing, the observer also considers the "strategic" direction of the work, coming up with ideas for improvements and likely future problems to address. This is intended to free the driver to focus all of their attention on the "tactical" aspects of completing the current task, using the observer as a safety net and guide.
Pair programming increases the man-hours required to deliver code compared to programmers working individually. Experiments yielded diverse results, suggesting increases of between 15% and 100%. However, the resulting code has about 15% fewer defects. Along with code development time, other factors like field support costs and quality assurance also figure in to the return on investment. Pair programming might theoretically offset these expenses by reducing defects in the programs.
In addition to preventing mistakes as they are made, other intangible benefits may exist. For example, the courtesy of rejecting phone calls or other distractions while working together, taking fewer breaks at agreed-upon intervals, or shared breaks to return phone calls but returning to work quickly since someone is waiting. One member of the team might have more focus and help drive or awaken the other if they lose focus, and that role might periodically change. One member might have knowledge of a topic or technique which the other does not, which might eliminate delays to find or test a solution, or allow for a better solution, thus effectively expanding the skill set, knowledge, and experience of a programmer as compared to working alone. Each of these intangible benefits, and many more, may be hard to accurately measure, but can contribute to more efficient working hours.
A system with two programmers possesses greater potential for the generation of more diverse solutions to problems for three reasons:
In an attempt to share goals and plans, the programmers must overtly negotiate a shared course of action when a conflict arises between them. In doing so, they consider a larger number of ways of solving the problem than a single programmer alone might do. This significantly improves the design quality of the program as it reduces the chances of selecting a poor method.
In an online survey of pair programmers from 2000, 96% of them stated that they enjoyed their work more than when they programmed alone and 95% said that they were more confident in their solutions when they pair programmed.
Knowledge is constantly shared between pair programmers, whether in the industry or in a classroom. Many sources suggest that students show higher confidence when programming in pairs, and many learn whether it be from tips on programming language rules to overall design skill. In "promiscuous pairing", each programmer communicates and works with all the other programmers on the team rather than pairing only with one partner, which causes knowledge of the system to spread throughout the whole team. Pair programming allows programmers to examine their partner's code and provide feedback, which is necessary to increase their own ability to develop monitoring mechanisms for their own learning activities.
Pair programming allows team members to share problems and solutions quickly making them less likely to have hidden agendas from each other. This helps pair programmers to learn to communicate more easily. “This raises the communication bandwidth and frequency within the project, increasing overall information flow within the team.”
There are both empirical studies and meta-analyses of pair programming. The empirical studies tend to examine the level of productivity and the quality of the code, while meta-analyses may focus on biases introduced by the process of testing and publishing.
A meta-analysis found pairs typically consider more design alternatives than programmers working alone, arrive at simpler more maintainable designs, and catch design defects earlier. However, it raised concerns that its findings may have been influenced by "signs of publication bias among published studies on pair programming". It concluded that "pair programming is not uniformly beneficial or effective".
Although pair programmers may complete a task faster than a solo programmer, the total number of man-hours increases. A manager would have to balance faster completion of the work and reduced testing and debugging time against the higher cost of coding. The relative weight of these factors can vary by project and task.
The benefit of pairing is greatest on tasks that the programmers do not fully understand before they begin: that is, challenging tasks that call for creativity and sophistication, and for novices as compared to experts. Pair programming could be helpful for attaining high quality and correctness on complex programming tasks, but it would also increase the development effort cost significantly.
On simple tasks, which the pair already fully understands, pairing results in a net drop in productivity. It may reduce the code development time but also risks reducing the quality of the program. Productivity can also drop when novice–novice pairing is used without sufficient availability of a mentor to coach them.
There are indicators that a pair is not performing well: